metadata
license: bigscience-bloom-rail-1.0
datasets:
- ehartford/wizard_vicuna_70k_unfiltered
- shahules786/orca-chat
- timdettmers/openassistant-guanaco
- laion/OIG
language:
- fr
- en
library_name: transformers
pipeline_tag: text-generation
widget:
- text: </s>Bonjour, qui es-tu ?<s>
- text: </s>Hello, who are you?<s>
base_model: cmarkea/bloomz-7b1-mt-sft-chat
tags:
- TensorBlock
- GGUF
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
cmarkea/bloomz-7b1-mt-sft-chat - GGUF
This repo contains GGUF format model files for cmarkea/bloomz-7b1-mt-sft-chat.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Prompt template
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| bloomz-7b1-mt-sft-chat-Q2_K.gguf | Q2_K | 3.201 GB | smallest, significant quality loss - not recommended for most purposes |
| bloomz-7b1-mt-sft-chat-Q3_K_S.gguf | Q3_K_S | 3.631 GB | very small, high quality loss |
| bloomz-7b1-mt-sft-chat-Q3_K_M.gguf | Q3_K_M | 4.137 GB | very small, high quality loss |
| bloomz-7b1-mt-sft-chat-Q3_K_L.gguf | Q3_K_L | 4.422 GB | small, substantial quality loss |
| bloomz-7b1-mt-sft-chat-Q4_0.gguf | Q4_0 | 4.505 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| bloomz-7b1-mt-sft-chat-Q4_K_S.gguf | Q4_K_S | 4.529 GB | small, greater quality loss |
| bloomz-7b1-mt-sft-chat-Q4_K_M.gguf | Q4_K_M | 4.907 GB | medium, balanced quality - recommended |
| bloomz-7b1-mt-sft-chat-Q5_0.gguf | Q5_0 | 5.328 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| bloomz-7b1-mt-sft-chat-Q5_K_S.gguf | Q5_K_S | 5.328 GB | large, low quality loss - recommended |
| bloomz-7b1-mt-sft-chat-Q5_K_M.gguf | Q5_K_M | 5.631 GB | large, very low quality loss - recommended |
| bloomz-7b1-mt-sft-chat-Q6_K.gguf | Q6_K | 6.202 GB | very large, extremely low quality loss |
| bloomz-7b1-mt-sft-chat-Q8_0.gguf | Q8_0 | 8.028 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/bloomz-7b1-mt-sft-chat-GGUF --include "bloomz-7b1-mt-sft-chat-Q2_K.gguf" --local-dir MY_LOCAL_DIR
If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:
huggingface-cli download tensorblock/bloomz-7b1-mt-sft-chat-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'